{"title":"利用方差的方差确定足够数量的Imputation:来自2012年NAMCS医师工作流程邮件调查的数据。","authors":"Qiyuan Pan, Rong Wei, Iris Shimizu, Eric Jamoom","doi":"10.4236/am.2014.521319","DOIUrl":null,"url":null,"abstract":"<p><p>How many imputations are sufficient in multiple imputations? The answer given by different researchers varies from as few as 2 - 3 to as many as hundreds. Perhaps no single number of imputations would fit all situations. In this study, <i>η</i>, the minimally sufficient number of imputations, was determined based on the relationship between <i>m</i>, the number of imputations, and <i>ω</i>, the standard error of imputation variances using the 2012 National Ambulatory Medical Care Survey (NAMCS) Physician Workflow mail survey. Five variables of various value ranges, variances, and missing data percentages were tested. For all variables tested, <i>ω</i> decreased as <i>m</i> increased. The <i>m</i> value above which the cost of further increase in <i>m</i> would outweigh the benefit of reducing <i>ω</i> was recognized as the <i>η</i>. This method has a potential to be used by anyone to determine <i>η</i> that fits his or her own data situation.</p>","PeriodicalId":64940,"journal":{"name":"应用数学(英文)","volume":"5 ","pages":"3421-3430"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4937882/pdf/","citationCount":"3","resultStr":"{\"title\":\"Determining Sufficient Number of Imputations Using Variance of Imputation Variances: Data from 2012 NAMCS Physician Workflow Mail Survey.\",\"authors\":\"Qiyuan Pan, Rong Wei, Iris Shimizu, Eric Jamoom\",\"doi\":\"10.4236/am.2014.521319\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>How many imputations are sufficient in multiple imputations? The answer given by different researchers varies from as few as 2 - 3 to as many as hundreds. Perhaps no single number of imputations would fit all situations. In this study, <i>η</i>, the minimally sufficient number of imputations, was determined based on the relationship between <i>m</i>, the number of imputations, and <i>ω</i>, the standard error of imputation variances using the 2012 National Ambulatory Medical Care Survey (NAMCS) Physician Workflow mail survey. Five variables of various value ranges, variances, and missing data percentages were tested. For all variables tested, <i>ω</i> decreased as <i>m</i> increased. The <i>m</i> value above which the cost of further increase in <i>m</i> would outweigh the benefit of reducing <i>ω</i> was recognized as the <i>η</i>. This method has a potential to be used by anyone to determine <i>η</i> that fits his or her own data situation.</p>\",\"PeriodicalId\":64940,\"journal\":{\"name\":\"应用数学(英文)\",\"volume\":\"5 \",\"pages\":\"3421-3430\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4937882/pdf/\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"应用数学(英文)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4236/am.2014.521319\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"应用数学(英文)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4236/am.2014.521319","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Determining Sufficient Number of Imputations Using Variance of Imputation Variances: Data from 2012 NAMCS Physician Workflow Mail Survey.
How many imputations are sufficient in multiple imputations? The answer given by different researchers varies from as few as 2 - 3 to as many as hundreds. Perhaps no single number of imputations would fit all situations. In this study, η, the minimally sufficient number of imputations, was determined based on the relationship between m, the number of imputations, and ω, the standard error of imputation variances using the 2012 National Ambulatory Medical Care Survey (NAMCS) Physician Workflow mail survey. Five variables of various value ranges, variances, and missing data percentages were tested. For all variables tested, ω decreased as m increased. The m value above which the cost of further increase in m would outweigh the benefit of reducing ω was recognized as the η. This method has a potential to be used by anyone to determine η that fits his or her own data situation.